code: def __init__(
      self, context: PyTorchTrialContext, hparams: Optional[Dict]
  ) -> None:
      self.scaler = context.wrap_scaler(GradScaler())
      super().__init__(context=context, hparams=hparams)
  
file_path: determined/harness/tests/experiment/fixtures/pytorch_amp/manual_amp_model_def.py
imports: from typing import Any, Dict, Optional, Sequence, Tuple, Union, cast
  import torch
  from torch.cuda.amp import GradScaler, autocast
  from train import MNistTrial
  from determined.pytorch import PyTorchTrialContext
label_desc: Use image node_id 1 to create a new MNistManualAMPTrial object from inherited base classes: MNistTrial with example: obj = MNistManualAMPTrial(context, hparams)